1. Technical Field of the Invention
The present invention is directed to improvements in noise suppression in telephony systems, particularly, to a system and method for distributed noise suppression.
2. Description of the Related Art
A communication system is comprised, at a minimum, of a transmitter and a receiver interconnected by a communication channel. Communication signals formed at, or applied to, the transmitter are converted at the transmitter into a form to permit their transmission upon the communication channel. The receiver is tuned to the communication channel to receive the communication signals transmitted thereupon. Once received, the receiver converts, or otherwise recreates, the communication signal transmitted by the transmitter.
A radio communication system is a type of communication system in which the communication channel comprises a radio frequency channel formed of a portion of the electromagnetic frequency spectrum. A radio communication system is advantageous in that the transmitter and receiver need not be interconnected by way of wireline connections. As, instead, the communication channel is formed of a radio frequency channel, communication signals can be transmitted between the transmitter and the receiver even when wireline connections therebetween would be inconvenient or impractical.
The quality of communications in a communication system is dependent, in part, upon levels of noise superimposed upon the information signal transmitted by the transmitter to the receiver. Noise can be introduced upon the informational signal at the transmitting side of the communication channel, e.g., acoustical background noise at the transmitting side. Noise can also be introduced upon the informational signal while being transmitted upon the communication channel, e.g., distortion introduced by speech coding and possibly also errors in the transmission channel.
When the noise level of the signal provided to a listener positioned at the receiver is high relative to the informational signal, the audio quality of the signal provided to the listener is low. If the noise levels are too significant, the listener is unable to adequately understand the informational signal provided at the receiver. Noise can be either periodic or aperiodic in nature. Random noise and white noise are exemplary of aperiodic noise. While a human listener is generally able to fairly successfully “block out” aperiodic noise from an informational signal, periodic noise is sometimes more distracting to the listener.
Various manners by which to remove noise components superimposed upon an informational signal, or at least to improve the ratio of the level of the informational signal to the level of the noise, are sometimes utilized. For instance, filter circuits are sometimes used which filter or otherwise remove the noise components from a communication signal, both prior to transmission by a transmitter and also subsequent to reception at a receiver.
Conventional filter circuits include circuitry for filtering noise components superimposed upon an informational signal. A spectral subtraction process is performed during operation of some of such conventional filter circuits. The spectral subtraction process is performed, e.g., by execution of an appropriate algorithm by processor circuitry. While a spectral subtraction process is sometimes effective to reduce noise levels, a spectral subtraction process also introduces distortion upon the informational signal. In some instances, the distortion introduced upon the informational signal is so significant that the utility of such a process is significantly limited. A spectral subtraction process is inherently a frequency-domain process and therefore necessitates a potentially significant signal delay when converting a time domain signal received by circuitry utilizing such a process into the frequency domain. Also, because such a process typically utilizes fast Fourier transform techniques, the resolution permitted of practical circuitry which performs such a process is typically relatively low.
When the ratio of the level of the information signal is high relative to the level of the noise, such noise suppression process, in spite of these problems, is typically fairly successful. However, when the ratio is high, there is also less of a need to perform noise suppression. Such a spectral subtraction process is therefore sometimes of a limited utility to significantly improve the quality of communications.
A radiotelephonic communication system is exemplary of a wireless communication system in which noise superimposed upon an informational signal affects the quality of communications transmitted during operation of the communication system. Noise can be superimposed upon the informational signal at any stage during the transmission and reception process including noise superimposed upon an informational signal prior to tis application to the transmitter. Such noise can deleteriously affect the quality of communications.
In particular, perceived speech quality of a signal containing background noise depends mainly on two factors: the level of the noise and any artifacts in the speech or noise.
A signal with less noise is generally considered more desired than a signal with a higher noise level and a noise suppression algorithm exploits this. When designing a noise suppression algorithm the overall perceived speech quality is, of course, optimized.
Separating the contributions of the noise level and speech impairments to the overall perceived speech quality, it has been shown that the noise level (in dB) has a fairly linear correspondence to the perceived quality, as generally depicted in FIG. 1 of the Drawings. Similarly, it can be shown that a noise suppression algorithm usually has a non-linear relation between the amount of noise suppression and the perceived speech quality due to impairments in the speech, as generally illustrated in FIG. 2. Hence, there is an optimum point for which the perceived speech quality may be maximized, as depicted in FIG. 3, which describes the sum of the two contributions to the speech quality described in FIGS. 2 and 3.
A fundamental problem in finding this optimum point is that although the general behavior depicted in FIGS. 1 and 2 holds for many noise types and users of the telephone system, the relative importance of the two contributions can vary substantially between different noise types and different users.
Particularly, designing for a very high noise power level reduction, the noise suppression algorithm will also affect the speech signal to a large extent, and this may cause an objectionable reduction of the perceived speech quality. Hence, if no, or only very minor, impact on the speech signal is desired, the noise suppression algorithm has to be tuned for a low amount of noise suppression.
There is, therefore, a need for improvement in noise suppression technology, particularly in view of the growing interconnectivity and ubiquity of telephonic devices in the world, where improvements in noise suppression algorithms and methodologies will facilitate further market penetration and increase customer quality perceptions.
It is in light of this background information on noise suppression algorithms and circuitry that the significant improvements of the present invention have evolved.